The Associate Director, Precision Medicine Data and Analytics position will involve developing clinical biomarker analysis plans in collaboration with biomarker and diagnostic leads, as well as conducting data analysis to summarize and interpret clinical trial data. This position will be also responsible for integrating clinical development objectives with global considerations into strategic business decisions and advanced data analytics for assigned programs in portfolio.

Key Responsibilities:

This role will provide YOU the opportunity to lead key activities to progress YOUR career, these responsibilities include some of the following…

• Oversee the analysis of complex biological data from clinical trials, ensuring robust interpretation and reporting for clinical study reports and regulatory submissions

• Support the delivery of clinical biomarker data analysis to enable Oncology Translational Medicine strategies and decision making towards identification of the right patient, right drug, right dose at the right time

• Integrate and analyze large-scale, high-dimensional, and multimodal biomarker datasets from internal and external sources to enhance our understanding of mechanisms of action, resistance, patient stratification and selection, new indications, and biologically driven combination strategies.

• Collaborate with CPMS, Diagnostic, Translational Research and AI/ML teams to ensure complementary data analytics approaches are evaluated and applied to deliver the most meaningful insights into the data

• Clear and timely communication of data analysis outputs and complex analytical principals & models to matrix team partners

• Maintain data integrity principles aligned with human data quality standards

• Support integration and analysis of academic biomarker partnership data and technology evaluation data generated by the Oncology Translational Medicine team

• Execute internal and external (e.x. real world data) biomarker data analysis to support pipeline growth, including life cycle management plans (e.x. biomarker prevalence in patient populations, right patient/dose), and leveraging data analytics outputs to support decision making.

• Execute advanced analytics and target/pathway analysis to support evaluation of due diligence business development asset evaluations.

Why you?

Basic Qualifications              

We are looking for professionals with these required skills to achieve our goals                                                                    ��      

• PhD degree or equivalent computational biology, bioinformatics, machine learning experience/training

• 5+ years of experience in Pharma/Biotech or academic setting.

• Experience with coding skills in R and/or Python and working knowledge of common bioinformatics databases, resources and tools

• Experience dealing with next-generation sequencing data and working with oncology drugs or programs

Preferred Qualifications:

      If you have the following characteristics, it would be a plus:

• Experience communicating analytical principles and results to non-analytical colleagues and stakeholders

• Experience working with and analyzing complex high dimensional datasets (e.x. single-cell and spatial transcriptomics, proteomics, cfDNA) by leveraging state of the art models and analytical approaches

• Experience with GCP principals and working on clinical studies

• Experience with data and metadata best practices (e.x. FAIR principals, data standards, cloud environment analytical tools)

• Experiencing creating data visualization outputs and working with multi-disciplinary teams

• Experience with statistical, analytical methods relevant to analysis of complex high dimensional heterogeneous datasets

• Experience with GitHub, development of R Shiny applications/R markdown, and working in cloud or high-performance computing (HPC) environments is a plus.

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